In 5G and beyond network architectures, operators and content providers base their content distribution strategies on Heterogeneous Networks, where macro and small cells are combined to offer better Quality of Service to wireless users. On top of such networks, edge caching and Coordinated Multi-Point (CoMP) joint transmissions are used to further improve performance. In this paper, we address the average delay minimization problem by first formulating it as a static optimization problem. Even though the problem is NP-hard we are able to solve it via an efficient algorithm that guarantees a $\frac {1}{2}$ -approximation ratio. We then proceed to propose two fully distributed and dynamic caching policies for the same problem. The first one asymptotically converges to the static optimal solution under the Independent Reference Model (IRM). The second one provides better results in practice under real (non-stationary) request processes. Our online policies outperform existing dynamic solutions that are PHY-unaware.

中文翻译：

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具有协调多点联合传输的小型蜂窝网络中延迟最小化的缓存策略

在 5G 及以后的网络架构中，运营商和内容提供商将其内容分发策略建立在异构网络上，其中宏蜂窝和小蜂窝相结合，为无线用户提供更好的服务质量。在此类网络之上，边缘缓存和协调多点 (CoMP) 联合传输用于进一步提高性能。在本文中，我们首先将平均延迟最小化问题表述为静态优化问题。即使这个问题是 NP-hard，我们也能够通过一个有效的算法来解决它 $\frac {1}{2}$ - 近似比率。然后，我们继续针对同一问题提出两种完全分布式的动态缓存策略。第一个渐近收敛到独立参考模型 (IRM) 下的静态最优解。在实际（非平稳）请求过程中，第二个在实践中提供了更好的结果。我们的在线策略优于现有的不支持 PHY 的动态解决方案。